Designing short term trading systems with artificial neural networks

Bruce Vanstone*, Gavin Finnie, Tobias Hahn

*Corresponding author for this work

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Abstract

There is a long established history of applying Artificial Neural Networks (ANNs) to financial data sets. In this paper, the authors demonstrate the use of this methodology to develop a financially viable, short-term trading system. When developing short-term systems, the authors typically site the neural network within an already existing non-neural trading system. This paper briefly reviews an existing medium-term long-only trading system, and then works through the Vanstone and Finnie methodology to create a short-term focused ANN which will enhance this trading strategy. The initial trading strategy and the ANN enhanced trading strategy are comprehensively benchmarked both in-sample and out-of-sample, and the superiority of the resulting ANN enhanced system is demonstrated.

Original languageEnglish
Title of host publicationAdvances in Electrical Engineering and Computational Science
Pages401-409
Number of pages9
Volume39 LNEE
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Electrical Engineering
Volume39 LNEE
ISSN (Print)18761100
ISSN (Electronic)18761119

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Vanstone, B., Finnie, G., & Hahn, T. (2009). Designing short term trading systems with artificial neural networks. In Advances in Electrical Engineering and Computational Science (Vol. 39 LNEE, pp. 401-409). (Lecture Notes in Electrical Engineering; Vol. 39 LNEE). https://doi.org/10.1007/978-90-481-2311-7_34